FAIR-EASE: the first interdomain digital architecture for integrated use of environmental data

In a world where all societal and scientific challenges are intertwined, it is urgent to launch multidisciplinary initiatives and projects so that scientists from different domains can collaborate. In order to carry out multidisciplinary projects, it becomes essential to develop gateways between metadata standards that will allow the matching of data representations designed for different domains. The opening of these gateways is therefore necessary for developing services across the disciplines, which is a key concept in the EOSC interoperability framework and the focus of the FAIR-EASE project.

FAIR-EASE focuses on opening these gateways for the earth and environmental sciences, which require a large volume of data from sources such as satellite, in-situ observations, models, and even omics experiments. Earth system domains are interconnected, but the present digital architecture is based essentially on distributed and domain-dependent data repositories inducing real difficulties for integrated uses of all the environmental data. This creates barriers for several studies with large societal impacts, such as climate change, agriculture and food, human safety and health.

To go beyond this state-of-the-art, the overall objective of FAIR-EASE is to customize and operate distributed and integrated services for observation and modelling of the Earth system, environment and biodiversity by improving their different components implemented in close cooperation with user-communities, the European Open Science Cloud (EOSC) and research infrastructures in their design and sustainable availability.

FAIR-EASE offers two services: the FAIR-EASE Interdisciplinary Data Discovery and Access service, that will provide users with an easy and FAIR service for discovery of and access to multidisciplinary and aggregated data sets, and the Earth Analytic Lab, that will provide users with an easy way to visualise, analyse and process environmental data on-demand, that is, according to their specific objectives, thematic, geographical areas and time periods of interest.

Earth and Environmental scientific communities are involved through the development of three multidisciplinary Use Cases that will define the community requirements from real-life science challenges.